Image Reconstruction for 3D Lung Imaging - Department of Systems ...

3.5 3D Considerations
In EIT it is often assumed that the injected currents stay in the two-dimensional electrode
plane [115]. This assumption has been used since the early days of EIT, however, it is
obviously incorrect since electric currents will spread out in three dimensions.
Reports of EIT in the clinical literature rarely use 3D EIT possibly due to the difficulty of
applying large numbers of electrodes and the high data collection rate needed for monitoring
physiological function. 3D reconstruction algorithms concerning medical applications can
be found in Gobel et al [59], Metherall et al [90], Polydorides [98], Polydorides and McCann
[99], Blue et al [22] and Molinari et al [91]. In three dimensions the possibilities for electrode
configurations and injection and measurement protocols are much larger than in 2D. With
cylindrical tanks a typical configuration is to use equally spaced electrodes arranged on
several parallel planes.
The main problem with 3D is computational: with three dimensional EIT the complexity
of body shapes and components requires a finite element model with a large number of
elements. Since the storage and computing time increase as a function of the number of
elements either the mesh discretization must be left too coarse to obtain images unaffected
by the element size or the mesh will so large that it causes the computer to run out of memory
during solution [91]. One either has to parallelize the problem onto several processors [21],
or investigate more efficient algorithms such as dual meshing [95]. The iterative Newton-
Raphson method is suitable for small-scale EIT problems. However it can be unsuitable for
large 3D problems where the number of elements can easily exceed 5000. This corresponds
to a matrix size of 25 ×10 6 or a memory requirement of 200 MB to store the matrix alone.
3.6 GOE MF Type II System
A detailed analysis on EIT hardware design and analysis can be found in [58][40][129]. The
first successful tomographic style impedance imaging was performed by Barber and Brown
in the early 80’s [15] using the Sheffield Mark 1 system [27] with the filtered backprojection
reconstruction algorithm. This is a 16 electrode adjacent drive system that measures 12.5
frames per second. The architecture of medical scanning equipment has not changed much.
For example Viasys Healthcare, Höchberg, Germany manufactures the Goe-MF II type
tomography system, which like the Sheffield Mk 1 has a single amplification unit and a
single detection unit that are multiplexed to 16 electrodes. Both are intended for use with
the adjacent constant current drive. The EIT group at Goettingen has improved the basic
system by optimizing some analog components and digitizing the signal at an earlier stage
of the processing. This has provided a large improvement in signal to noise ratio of the
EIT signal. In [62] they reported that the Goe-MF type II provides an order of magnitude
improvement in SNR over the Sheffield Mk 1. Like the Sheffield Mk 1 this machine is
intended to be used to collect 2D data from a planar set of 16 electrodes equispaced around
the thorax. The default reconstruction algorithm is a functional image based on individual
frames reconstructed using filtered backprojection [62]. However the raw measurement data
can be exported for use with algorithms not included with the Goe-MF II. This machine
was used to obtain empirical data used to verify some of the work in this thesis.
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